Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Estimating sample sizes for continuous, binary, and ordinal outcomes in paired comparisons: practical hints.

S A Julious1, M J Campbell, D G Altman

  • 1Clinical Pharmacology Data Sciences, Glaxo Wellcome, Greenford, London, UK.

Journal of Biopharmaceutical Statistics
|June 24, 1999
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

CONSORT 2010 statement: extension checklist for reporting within person randomised trials.

The British journal of dermatology·2019
Same author

'Allocation concealment': the evolution and adoption of a methodological term.

Journal of the Royal Society of Medicine·2018
Same author

[Better Reporting of Interventions: Template for Intervention Description and Replication (TIDieR) Checklist and Guide].

Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))·2018
Same author

GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research.

Research involvement and engagement·2017
Same author

GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research.

BMJ (Clinical research ed.)·2017
Same author

Quality control of ultrasound for fetal biometry: results from the INTERGROWTH-21<sup>st</sup> Project.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology·2017

Calculating sample size for paired studies is crucial but often overlooked. This article provides simple formulas for sample size calculations in matched or paired studies with continuous, binary, or ordinal outcomes.

Area of Science:

  • Biostatistics
  • Clinical Trials Methodology
  • Epidemiology

Background:

  • Sample size calculations are essential for study validity but rarely reported for paired designs.
  • Paired data are common in crossover trials and matched case-control studies.
  • Editor recommendations emphasize the need for justified sample size calculations.

Purpose of the Study:

  • To provide simple formulas and strategies for sample size calculations.
  • To address the gap in sample size reporting for paired studies.
  • To guide researchers in planning matched or paired studies.

Main Methods:

  • Description of simple formulas for sample size estimation.
  • Strategies applicable to various outcome types (continuous, binary, ordinal).

Related Experiment Videos

  • Focus on calculations for matched or paired study designs.

    • Main Results:

    • Formulas are presented for calculating the required number of patients.
    • Methods accommodate continuous, binary, and ordinal outcome measures.
    • Strategies are designed for simplicity and practical application.

    Conclusions:

    • Researchers can now utilize straightforward methods for sample size determination in paired studies.
    • This work supports the justification of sample sizes in matched and crossover designs.
    • Improved sample size planning enhances the statistical power and reliability of paired study findings.